Most motors operate in dynamic environments where load torque changes during operation. For example, a milling motor on a milling machine is routinely subjected to changing load torque as the characteristics of a workpiece, including hardness, brittleness, consistency, and temperature, change during the milling process. A motor controller must compensate for the load torque in order to produce a desired motor velocity.
In determining how control torques should be altered to correct motor velocity two parameters must be considered and balanced; (1) correction quickness and (2) correction accuracy. Clearly it is desirable to eliminate the velocity error as quickly as possible. However, quick correction often results in an inaccurate velocity correction that initially overshoots or undershoots the desired speed and then oscillates about the desired speed for a period before reaching a steady state. Thus, there is a tradeoff between correction speed and correction accuracy.
Some motor applications require extremely accurate torque correction. For these applications, large velocity overshoots or undershoots during correction are unacceptable. For example, a velocity overshoot or undershoot might drive a machine tool that forms precise cuts in a workpiece into an incorrect position, might drive a robotic mechanism into a workpiece or other equipment, or might increase or decrease the tension between rolls used to collect, or disperse sheet material. Each of these examples could easily damage or destroy workpieces or machines and thus cannot be tolerated.
Control torque can be altered to effect motor velocity correction more quickly and to limit the extent to which corrected velocities overshoot or undershoot desired velocities. However, difficult to measure motor and load characteristics may reduce or exaggerate the effects of a control torque change on motor speed and accuracy and make it extremely difficult to determine how torques should be altered. In particular, if motor and load inertia, referred to herein as plant inertia, is not accounted for the effect of control torque changes may be dampened or exaggerated to an unknown extent. Unfortunately, plant inertia is often impossible to directly measure.
With a motor rotor, when the rotor is rotating in steady state at a desired velocity and the load torque changes, the motor velocity changes. Assuming the load torque is increased, the velocity would decrease. In order to return to the desired velocity the control torque to the motor would have to be increased to compensate for the change in load torque. The plant inertia which would tend to maintain the plant at the lower velocity. Often, inertia compensation is also required when motor velocity is increased deliberately by a user instead of as a reaction to a velocity error. For example, it may be desirable to step motor speed up from 100 rev/sec to 200 rev/sec. If the motor is accelerated at a constant rate up to 200 rev/sec, the plant inertia can drive the motor velocity past 200 rev/sec which might not be acceptable if precise velocity changes are required.
The industry has developed different types of adaptive control systems to compensate for both motor inertia changes and load torque disturbances. One type of commonly designed adaptive control system is model reference adaptive control (MRAC) that includes a reference model that generates an ideal motor output which is compared to an actual motor output to generate an error signal. MRACs also include adaptation mechanisms that receive the error signals and alter controller gains to compensate for the error and change motor operation accordingly.
Some MRACs have been designed to derive an inertia estimate from the control error signal and use the inertia estimate to alter controller gains in an effort to better control motor velocity. While these systems have improved the speed with which motor velocity can be altered and controlled accurately, they still have two significant deficiencies.
First, in order for the inertia estimate to be useful, the estimate must be accurate. The best inertia estimates presently used have relied on an iterative approach that mathematically combines a torque factor and an acceleration or velocity factor.
Second, present methods of employing estimated inertia are indirect and thus limit the value of the estimate. Inertia estimates are usually plugged into transfer functions or other complex equations to produce gain modifying signals that are indirectly related to the inertia estimate. While the gain modifying signals are useful, by employing the inertia estimate indirectly, these methods lose sight of the parameter of interest, inertia. Furthermore, each additional calculation used to derive a controller gain introduces additional sources of error into the gain figure.
Thus, it would be advantageous to have a motor controller that can accurately determine an estimated plant inertia and that can use the inertia estimate to directly regulate control torque delivered to a motor.